August 9, 2026

The Level Four Line

Today’s essay argues that clinical judgment compresses into something faster than language, and that the real bottleneck is writing the spec. So this takes the best case: “was that office visit moderate complexity?” — the one clinical judgment America has tried hardest to specify, with a written definition, a 2021 rewrite, a decision table, audits, and money attached. 1,440 clinicians, one dot each, plotted by established-visit volume against the share they coded at level 4 or 5 (99214/99215) rather than level 2 or 3. Filter by any of sixteen specialties, switch the vertical axis, and drag the minimum-volume slider. The critical lens is the interaction: CMS suppresses every provider–code row covering ten or fewer beneficiaries, so a cardiologist with 400 level 4s and eight level 3s appears at 100% — among clinicians with 11–49 visits, 79.9% have only one of the four codes present and 85% sit at exactly 0% or 100%. Push the slider and that bimodality dissolves on cue: the rails fall to 10%, the single-code column falls to 4%. And the spread underneath does not move. Among the 11,558 clinicians billing more than 1,500 established visits a year — too busy to be a rounding artifact, too visible to skip an audit — the middle half still runs 27% to 90%. A second dense graphic ranks all 31 specialties with 1,000+ clinicians by their 10th–90th percentile band: podiatry’s median is 6.6%, endocrinology’s is 95.1%, and the shortest bar on the board is still thirty points wide. Ends where the essay does: the spec is the deliverable, and it is the part nobody can write for you.

Data explorer

Show Me the Spec

Source: Barbara Hays & Cindy Hughes, “Coding Level 4 Office Visits Using the New E/M Guidelines”, AAFP Family Practice Management, Jan/Feb 2021 · MIMI Labs: CMS Medicare Physician & Other Practitioners PUF, by Provider and Service, 2024

The same finding as a single animated graphic. 1,440 clinicians start stacked on one point — where a working specification would put them — and one button releases them into their actual 2024 numbers. The field opens to a 67-point interquartile range with a visible pile-up against both walls, and the readouts count up as the dots fly. Below it, the same clinicians split into volume bands with a step-through button: at 11–49 visits 89% are pinned to a wall, which is CMS’s ten-beneficiary suppression rule rather than clinical practice; by 500+ visits the walls are down to 14% and the middle-half spread is unchanged. National figures on all 540,972 clinicians sit underneath in a table. The piece is deliberately careful about what this is not: an older panel, a referral-heavy practice, longer slots and a good scribe all legitimately move this number, and claims data cannot separate judgment from documentation habit. But that concession is the argument — nobody can write down how much a scribe should shift your coding either. Those are reflexes too, which is exactly why the “learn to code” advice was always the wrong assignment.

Graphical narrative
August 8, 2026

Nine Point Nine Billion Dollars of Bandage

Medicare Part B paid $9.86 billion for skin substitutes in 2024 — more than it paid for ambulances or anesthesia — up from $23.9 million across 16 codes in 2013. Here are the 600 highest-billing clinicians in the country, one dot each, plotted by square centimeters of graft billed against Medicare allowed dollars per square centimeter, with the CY2026 flat rate of $127.28/sq cm drawn as a line near the floor. Filter by specialty, state, or minimum volume; switch the axes to dollars per patient or total allowed; then press “2026 flat rate” and watch the whole field drop onto the line — the same 2.9 million square centimeters, the same wounds, repriced from $4.39 billion to $369 million, a 91.6% cut with nothing clinical changed. Nurse practitioners are the single largest billing block at $1.64 billion across 372 clinicians. Critical lens built in: CMS suppresses every clinician-product row covering ten or fewer beneficiaries, so only $4.62B of the $9.86B (47%) is visible at individual level and the invisible half is by construction the low-volume half; the patient counts are summed across product codes and double-count anyone treated with more than one graft, which the page says outright rather than quietly using; and the minimum-volume slider is there to be pushed — watch the live log–log correlation readout wander once you are fitting forty points instead of six hundred. Ends on the price comparison that explains the whole thing: Apligraf, PMA-approved since 1998, has been paid $29–$39/sq cm for twelve straight years; Amchoplast was paid $4,160/sq cm in 2024. Same procedure, 138× the price, and the difference is which payment methodology the product qualified for.

Data explorer

The Price Ladder

Sixty-nine Q4‑series skin substitutes, every one a sheet of processed tissue laid on a chronic wound, every one billed to Medicare in 2024 — on a single dot field, price per square centimeter against total spend, sized by patients treated. The spread runs from $30 to $4,160 per square centimeter. One button reprices the entire field at the CY2026 flat rate and $9.84 billion becomes $905 million, a 90.8% cut that lands within a point of CMS's own estimate. Underneath, two more graphics: twelve years of Apligraf's allowed amount sitting flat between $29 and $39 while Q4205 — the largest single code in the country at $1.44 billion — jumps from $349 to $1,424 in one year, and the national spending bars from $23.9M across 16 codes in 2013 to $9,858M across 94 in 2024 with beneficiaries rising only tenfold over the same span. Critical lens: the repricing is arithmetic, not a forecast — it holds 2024 volume constant, which is exactly the thing the rule is designed to change; 25 codes below $5M are omitted (0.2% of spend); rows with ten or fewer beneficiaries are suppressed by CMS entirely; and the “patients” counts double-count anyone who received more than one product. The takeaway generalizes past wound care: any payment methodology that derives a price from the seller's own reported price gets gamed, and the tell is always spending growing an order of magnitude faster than patients.

Graphical narrative
August 7, 2026

The Ruler’s Own Ruler

Source: Aali et al., “MedVAL: Toward Expert-Level Medical Text Validation with Language Models” · npj Digital Medicine, Aug 4, 2026 (DOI 10.1038/s41746-026-03084-5) · all 90 model×task cells from Tables 2, 3a, 3b, S2, S3 · MIMI Labs: Dartmouth Atlas MEDPAR ICD‑10 principal diagnoses, 2018 · code StanfordMIMI/MedVAL, benchmark MedVAL-Bench

A Stanford group open-sourced the thing everyone said was missing: an evaluator that checks whether AI-generated clinical text is factually consistent with its input, trained without a single physician label, with a 4B model you can run on a laptop. Ten language models were scored against MedVAL‑Bench and five were also distilled — 90 model‑by‑task cells, every one plotted here, against your choice of average input length, inter-physician agreement, or task size. Set the axis to agreement and show MedVAL GPT‑4o and you reproduce the paper’s r = 0.67: the evaluator scores highest exactly where the physicians agreed with each other most. Then click query2question to drop it and the correlation doesn’t weaken — it inverts to r = −0.55. One task out of six, the one where twelve physicians reached only α = 0.560 among themselves, was carrying the whole relationship; push the minimum-task-size slider to n ≥ 135 and you are fitting three points at r ≈ 1.0, which means nothing at all. Critical lens throughout: the abstract’s headline F1 of 66% → 83% is the binary safe/unsafe judgment, while the four-class risk grade a reviewer would actually act on moves 36.7% → 51.0%; the non-inferiority claim rests on 90 of 840 examples, tests GPT‑4o rather than the released 4B, and never prints the observed Δ, the confidence bound, or the human expert’s own score. Scale check from MIMI Labs: 11,007 distinct ICD‑10 principal diagnosis codes appeared across 12.2M Medicare inpatient stays in 2018 — 840 examples would touch 7.6% of them.

Data explorer

840 Dots

Source: Aali et al., “MedVAL: Toward Expert-Level Medical Text Validation with Language Models” · npj Digital Medicine, Aug 4, 2026 (DOI 10.1038/s41746-026-03084-5) · counts from Tables 2 and S3 · benchmark MedVAL-Bench, weights MedVAL-4B

Everything the new evaluator knows about being wrong comes from 840 physician-annotated outputs. Here they are — all of them, one dot each, six task columns, built by a single animated field with no click-through. Colour them by the four-level physician risk grade (44.4% of the benchmark is graded level 3 or 4, meaning a human must review or rewrite); by which three tasks were held out of distillation entirely (395 of 840); or by input length. Then light up the 90 dots — fifteen per task — that were read by more than one physician. That 10.7% subset is the entire basis for the inter-physician agreement figures and for the headline that the evaluator is non-inferior to a human expert; the paper says so in its own limitations section. Below the field, the six tasks’ average input lengths drawn to scale: 10, 50, 69, 82, 543 and 1,497 tokens — the medication-answer task, where distillation produces its largest gains, hands the evaluator a ten-token question, and its bar is 0.7% the width of the ambient-scribe task’s. A real ED encounter is not a paragraph; it is a chart. Critical lens: on query2question the physicians reached only α = 0.560 with each other, and the paper reports r = 0.67 between how well physicians agreed on a task and how well the tuned model scored on it — the evaluator looks most expert where experts find it easiest to agree. What didn’t get distilled is the taxonomy: four risk levels, eleven named error types, twelve physicians, and a decision about what each kind of wrongness costs.

Graphical narrative
August 6, 2026

The Underwater Line

Buried in the FY 2027 inpatient rule CMS published on August 4: the repeal of the alternative pathway that let an FDA Breakthrough Device designation stand in for proof of substantial clinical improvement when applying for a New Technology Add-on Payment. That reads like paperwork; it is a pricing constraint. Medicare pays one fixed amount per inpatient stay, set by the stay's MS‑DRG, regardless of what the hospital spent — so every dot here is one of the 773 national MS‑DRGs, average Medicare payment against annual discharges, and the slider is the cost of the new thing you want to put inside that stay. At $25,000 with no add-on payment, the technology costs more than the entire average Medicare payment in 620 of 773 DRGs — 6.09 million discharges, 88% of all Medicare fee-for-service inpatient volume. Turn NTAP on at 65% and the underwater count falls to 220 DRGs and 2.22 million discharges. That gap, 620 versus 220, is the add-on payment. The rule didn't remove NTAP; it removed the shortcut to qualifying for it, for applications submitted on or after October 1, 2026. Stress test: flip the axis toggle to Charges and the red mostly disappears — at a $50,000 technology only 196 DRGs sit below the line by charges against 729 by payments, because the median DRG's submitted charge is 6.0× its Medicare payment, which is why a market model built off chargemaster data invents roughly four times the headroom that exists. And drag min annual discharges up: 729 underwater becomes 482 at 1,000/yr and 243 at 5,000/yr, because 263 of the 773 DRGs see fewer than 1,000 discharges nationally and together carry 1.6% of volume. Critical lens: NTAP is calculated off the hospital's cost for the case, and this file contains payments and charges and no cost column at all — so the red-dot test is a ceiling test, not a margin test.

Data explorer

773 Prices

On July 8, FDA and CMS officials hosted an unannounced “clinical AI demo day” at White Oak; STAT reviewed the agenda and published it August 5. Ten companies, no health system, no specialty society — and the agenda covered not only whether the tools are safe but how Medicare should pay for them. This is that second question, drawn. One animated field, no click-through: it plays itself and you can scrub back. All 773 national MS‑DRGs arrive as a scattered cloud, settle into a dot histogram sorted by what Medicare actually pays, the median line lands at $12,714, and then a technology-cost line sweeps in from $300,000 down to $25,000 while the dots it can no longer fit inside turn red and a live counter runs. At $25,000 with no add-on payment that is 620 of 773 prices and 88% of all Medicare fee-for-service inpatient volume; with NTAP at 65% it is 220 and 32%. Then the last act: an empty box where autonomous clinical AI would sit — no DRG, no code, no rate, 0 of 773 rungs — because when no clinician performs the service, no existing payment category contains it, and whoever defines “a unit of service” sets the business model for the whole category. Sliders hand control back after the story ends. Critical lens: these are payments, not costs, and NTAP is computed off costs, so the red is a ceiling test not a margin test; fee-for-service only, so Medicare Advantage — roughly half of enrollees — is absent; and 263 of the 773 DRGs see under 1,000 discharges a year and carry 1.6% of volume, so a dot is a row, not a population.

Graphical narrative
August 5, 2026

Clinics Like Mine

Magan checked forty-one references against their primary sources and found every landmark ambient-scribe study ran at UCLA, Mass General Brigham, Emory, UCSF, Yale, UC Davis, Kaiser Northern California, Penn or Stanford — and none in a federally qualified health center. So here is the population that isn't in the evidence, all of it on one scatter: every HRSA grantee in the country, panel size (log) against the share of patients HRSA records as best served in a language other than English. 8,977,620 patients — 27.8% of the national panel — sit on that axis, and 190 grantees are above 50%. Filter by state, urban/rural, and language share; the readout recomputes the weighted share, the correlation, and the study count (0). Stress test: the scatter tilts at r = 0.205, which reads as “scale correlates with linguistic diversity” — drag min panel size to 20,000 and r collapses to 0.115, because the tilt was the long tail of 552 rural grantees at a 3.4% median. Critical lens: “best served in another language” is a self-reported UDS field, not an audio measurement — it says nothing about accented English, which is exactly where a scribe pipeline degrades; the grain is the grantee, not the clinic; and the zero is a hand-assembled absence (“none found,” not “none exist”).

Data explorer

Nine and 1,352

One animated field, no click-through — it plays itself and you can scrub back. 1,352 health center grantees arrive as an undifferentiated cloud, then sort themselves into a dot histogram along the share of patients best served in a language other than English, then the 499 above 25% light up (they carry 16.4 million patients, half the national panel from a third of the dots), then the nine academic settings where the ambient-scribe evidence was actually generated slide in underneath as nine navy squares with nothing above them. Alongside: the 2020 PNAS audit of five commercial speech-recognition systems — word error rate 0.35 for Black speakers against 0.19 for white speakers, a gap nobody has re-tested in any of the 1,352. Critical lens: one dot is one grantee, not one clinic and not one patient, so the tall left stack over-represents small rural organizations; the language field is self-reported and blind to accent; and the nine is an absence assembled by hand from 41 checked references.

Graphical narrative
August 4, 2026

The Accountability Object

Source: STAT First Opinion — Chaudhry & Valentine Theard, FSMB, “AI is not ready to be licensed like a physician” (Aug 3, 2026) · MIMI Labs: NPDB Public Use Data File (updated May 2026) · 193,023 paid malpractice claims, incident years 2004–2021

The Federation of State Medical Boards argued this week that a license isn't a certificate of correctness — it's a name to attach when something goes wrong. So look at the federal database of those names: 1,911,185 disclosable reports, 985,019 practitioners, zero models. Every paid malpractice claim cut two ways at once — what was alleged (11 groups) × what happened to the patient (10 severity codes) — as 110 dots on a log-log scatter of claim count against mean payment. The four groups a decision-support tool actually sits inside (diagnosis, treatment, medication, monitoring) carry 63.8% of paid claims and 60.5% of the dollars. Stress test: drag the minimum-claims filter to 200 and the expensive-looking top-right corner empties — IV & blood products → brain damage reads $875k a claim on 17 claims, sitting beside signals built on thousands. Critical lens: payments are coded range midpoints not dollars, incident years 2020–21 are hollowed by reporting lag, work-state is null in 57% of records, nine states double-file state-fund payments — and there is no field anywhere in the schema for “a model contributed to this decision.”

Data explorer

A Name to Attach

Source: STAT First Opinion — FSMB on licensing AI (Aug 3, 2026) · MIMI Labs: NPDB Public Use Data File · 1,930 dots at 100 paid claims each

193,023 paid malpractice claims arrive as an undifferentiated haze, then settle into what was alleged, then re-settle into what it cost the patient. Three beats, one animated field, no click-through required — it plays itself and you can scrub back. The four allegation columns a clinical AI tool would land inside light up red; death turns out to be the single largest severity code in the file. Alongside: 1,911,185 NPDB reports, 985,019 practitioners named, 0 models named. Critical lens: at 1 dot = 100 claims the rare categories vanish (IV & blood products is four dots across eighteen years), the dollars are coded band midpoints, and paid claims record legal outcomes filtered through two decades of tort reform — not harm.

Graphical narrative
August 2, 2026

The Calm Light

Source: CMS — Hospital Readmissions Reduction Program · MIMI Labs: HRRP public file, latest vintage, Provider Data Catalog · READM-30-HF-HRRP, discharges Jul 1 2021 – Jun 30 2024

CMS publishes two numbers for every hospital and only one of them is arithmetic. Divide readmissions by discharges and a Tennessee hospital with 31 heart-failure discharges reads 45.2%; CMS's own published rate for the same hospital, same period, is 21.5%. All 2,316 non-suppressed hospitals on one funnel plot — toggle between the number you can compute and the number that carries the money, and watch the spread fall from SD 5.55 to 2.44 without a single hospital changing. Stress test: drag the minimum-discharge slider and the “worst in America” leaderboard turns over completely — of the 50 highest raw rates, median volume is 65 discharges against 274 for the file as a whole. Critical lens: 36% of HRRP rows are suppressed outright, the denominator excludes Medicare Advantage (now >half of Medicare), and CMS conceded its own risk model was scoring poverty when it added dual-eligible peer groups in FY2019.

Data explorer

Twenty-Three Points

Source: CMS — Hospital Readmissions Reduction Program · MIMI Labs: HRRP public file, all six conditions, 8,037 hospital-condition rows

2,316 dots drop in at the readmission rate anyone can compute from the file, then red segments draw the distance to the rate CMS actually publishes, then they land on it and the left-hand chaos disappears. The median correction is 3.73 points under 75 discharges and 0.45 points at 600 or more; the largest single move is 23.68 points. Then all six HRRP conditions as small multiples — and the honest finding that the funnel only behaves in four of them: CABG and hip/knee have 363 and 253 hospitals and their percentile bands wobble instead of narrowing, so those panels are marked in red with their bucket sizes shown. Critical lens: shrinkage is a choice, and it guarantees a genuinely bad small hospital reads as average — neither published number tells you which one you're looking at.

Graphical narrative
August 1, 2026

The 3.5 Line

All 610 Medicare Advantage contracts with 1,000+ members on one brushable scatter — 2026 star rating against enrollment, sized by members, 35.7M people. Humana said the 2027 exits are "mostly plans rated 3.5 stars or lower." Below that line sit 11,165,479 members nationally, and 4,233,892 of them are Humana's — 59.6% of its own book and 37.9% of every low-star MA member in the country. The announced 600,000 is 14.2% of it; Humana's single largest contract, H5216, is four times the whole exit and stays. Stress test: star rating vs. log enrollment gives r = +0.35 across 486 rated contracts and decays to +0.22 once you drop everything under 50,000 members. Critical lens: 378 contracts (42.9%) carry no overall rating at all, and we could not reproduce Humana's own "20% of members in 4-star plans" from the public files — we get 38.6%.

Data explorer

Fourteen Percent

Source: Becker's — Humana CFO Celeste Mellet, July 29 Q2 earnings call, published Jul 30, 2026 · MIMI Labs: CMS CPSC enrollment June 2026 × 2026 Medicare Part C & D Star Ratings

1,788 dots, one per 20,000 Medicare Advantage members, settling into their star bands — then Humana's 7.1M turn red, then the 600,000 exit gets bracketed as 30 of them, then 40% fade back because that's the recapture rate Humana expects. Humana's 3.5-star band alone holds 3,590,176 people, 40.7% of everyone in the country at 3.5 stars; it has zero members at 5.0 and zero at 2.0, while Kaiser has zero below 4.0. Then the part national averages hide: 57% of every MA member in Montana is in a Humana contract rated 3.5 or lower, versus 3.9% in California. Critical lens: the star rating is a lagged contract-level bonus-payment composite, not a quality reading of your attributed lives.

Graphical narrative
July 31, 2026

The Ex Parte Line

Source: Tradeoffs — "Meet the Man Launching Trump's Medicaid Work Requirements Months Early" (Jul 30, 2026) · CMS-2454-IFC, effective Jul 31 · MIMI Labs: CMS Medicaid & CHIP Eligibility Processing, state-month renewal outcomes, Mar 2023–Apr 2025

All 51 reporting jurisdictions on one brushable scatter — ex parte renewal rate against procedural coverage loss, sized by volume, 69.1M renewals. Texas clears 11.8% of renewals without asking anyone for a document; Washington clears 80.6%. Nationally 8.49M people lost Medicaid on paperwork versus 4.69M found actually ineligible — 1.81 paperwork losses per ineligibility finding. Stress test: filter to states under 300k renewals and 2024–25 gives r = −0.84, a gorgeous finding that collapses to r = −0.08 when you toggle to the unwinding. All 51 states hold steady at about −0.49 in both periods. Critical lens: the dataset has 22 columns and not one of them is the medically-frail exemption code list that decides who is too sick to work.

Data explorer

The 26%

Source: Tradeoffs — Nebraska Medicaid director Drew Gonshorowski, published Jul 30, 2026 · MIMI Labs: CMS Medicaid & CHIP Eligibility Processing, renewal outcomes May 2024–Apr 2025

1,000 dots per state, drawn to the real CMS renewal ledger, animating into the split that decides everything: 55 cleared from data the state already held, 45 who had to act. Of the 31.0M renewals the automation could not clear, 27.4% ended in a procedural termination; of the 38.0M it cleared, none did, by definition. Then the trap — Washington has the country's highest ex parte rate (80.6%) and the third-highest loss rate inside its un-cleared cohort (54.7%), while Pennsylvania is second-worst on automation and best on that measure. Automate harder and what's left is the hard cases. Rank states on the bar chart alone and you rank them backwards.

Graphical narrative
July 29, 2026

Cleared Before Measured

Source: Chalouhi et al., npj Digital Medicine — multireader fetal ultrasound study (Jul 28, 2026) · MIMI Labs: FDA 510(k) release, imaging-AI product codes, decisions through Jul 17, 2026

Every FDA 510(k) clearance in the imaging-AI product codes — 369 dots, 184 companies, 2016 to July 2026 — plotted against review time, colored by what the device is allowed to claim. Only 20% sit in a detection/diagnosis code; more than half just segment and measure. Stress test: raise "min clearances per company" to 5 and the median review drops 140 → 123 days; filter to each company's first submission and it climbs to 172. Critical lens: nothing in the 510(k) record says whether anyone ever ran the unassisted arm — Sonio Suspect cleared in 91 days and published its 522 days later.

Data explorer

The Unassisted Arm

Source: Chalouhi et al., npj Digital Medicine, published Jul 28, 2026 · device: Sonio Suspect, FDA K243614 · study funded by Sonio, a Samsung company

All 750 fetal ultrasound stills from yesterday's multireader study on one field — 250 abnormal, 500 normal — with the AI switching on and off. Unassisted, 13 U.S. physicians caught 136 of 250 abnormalities and agreed with each other 26% of the time; with the assistant, 221 and 72%. Then the stress test the study didn't run: drag prevalence from the enriched 33.3% down to a real 3% anomaly screen and watch PPV fall from 78.5% to 18.4% — roughly four false alarms for every real finding, even in the assisted arm.

Graphical narrative
July 28, 2026

The Blast Radius Ledger

Source: Becker's — health IT vendor breach exposes 425,000+ patients (Jul 2026) · AnMed systems disruption (Jul 26–27, 2026) · MIMI Labs: HHS OCR breach portal, filings of ≥50,000 people, Oct 2009–May 2025

Every large breach ever reported to HHS — 939 filings, 586 million records — on one brushable scatter, vendor-linked breaches in red. Raise the floor from 50k to 5M and watch the everyday provider breaches vanish while the vendor detonations remain: red's share of affected people grew 18% → 63%. Critical lens: the vendor is never named in the file, and the biggest breach in history (Change Healthcare, ~190M) is missing from the snapshot entirely.

Data explorer

One Vendor, Many Letters

Source: Becker's — health IT vendor breach (Jul 2026) · AnMed update (Jul 27, 2026) · MIMI Labs: HHS OCR breach portal, ≥50k filings, 2009–2025

Sixteen years of breach filings replayed as a monthly dot field: a hospital breach makes one dot, a vendor breach makes a tower. Watch three detonations — AMCA (14 letters, one month), Blackbaud (40 letters, one month), MOVEit (a seven-month tail) — surface under other organizations' names, with this week's AnMed and Unlimited Technology Systems dots drawn where they'll land. The vendor's name appears in the ledger zero times.

Graphical narrative
July 27, 2026

The Predicate Lane Economy

Source: Federal Register, 91 FR 46719 — FDA final order codifying the diabetes digital behavioral therapeutic device (Jul 24, 2026) · MIMI Labs: FDA device classification (foiclass) + 510(k) databases, decisions 2016–Jul 2026

FDA maintains 6,987 product-code lanes; 78% carried zero 510(k)s in a decade. All 846 lanes with real traffic on one brushable scatter — traffic vs. median FDA review days, one dot per lane, the 13 digital-therapeutic lanes in red with QXC (Friday's new diabetes lane) on the zero shelf. Critical lens: drag the sample-size floor and watch the "fastest lane in FDA" dissolve into small-n noise.

Data explorer

Thirteen Lanes, Fifteen Cars

Source: Federal Register, 91 FR 46719 (Jul 24, 2026) · MIMI Labs: FDA 510(k) database, all "Substantially Equivalent" decisions through Jul 2, 2026

Every digital-behavioral-therapeutic lane FDA has opened, drawn as a lane — and every 510(k) that ever drove through one as a dot. Thirteen lanes, fifteen clearances ever, five lanes empty, including the diabetes lane codified Friday. For scale: one radiology software lane (LLZ) carries 442 — 29× all thirteen combined. A lane is not a market.

Graphical narrative
July 25, 2026

Billing the Algorithm

Source: AAPC — "AMA Posts CPT Early Release Codes" (effective July 1, 2026) · AMA — CPT codes for AI-enabled services · MIMI Labs: Medicare Physician & Other Practitioners, national rows, CY2018–CY2024

The mid-year CPT release is where AI codes land first — so which ones does Medicare actually pay? 27 AI-adjacent codes checked against seven years of Part B physician claims, one dot per code, animated by year: the whole 2024 "billable AI" market is $10.0M, 12 of 25 AI codes never clear the 11-patient floor (including 0691T, today's Money Plumbing example), and the algorithmic-ECG code earned $3.53 a run — once. Critical lens: a small-n filter that dissolves most of the "growth," plus the physician-claims blind spot stated out loud.

Data explorer

The Code Exists. The Check Doesn't.

Source: AAPC — "AMA Posts CPT Early Release Codes" (effective July 1, 2026) · MIMI Labs: Medicare Physician & Other Practitioners, national rows, CY2013–CY2024

Twelve years of AI billing codes as one animated chart: the six-year Category III valley (FFR-CT never topped 16k family-wide services), the 2024 conversion spike to 29,270 services and $7.3M as 75580, autonomous retinal AI's price falling $32→$27 while the human-read version still outbills it — and a ghost shelf of 12 codes that never registered eleven national patients. Conversion, not code creation, is the revenue event.

Graphical narrative
July 24, 2026

The Quarter-Billion Reshuffle

Source: CMS — CY2027 Physician Fee Schedule proposed rule (comment window open) · MIMI Labs report + queries: Medicare Physician & Other Practitioners, CY2024 extract + FFS Part B enrollment extract 2025-06-30

CMS proposes to reshuffle the remote-monitoring codes — five years after standardized payment grew from $5.36M to $259.1M (48×, 389k device-supply patients, 17k management clinicians). Every state's RPM footprint as one dot: adoption per 10k FFS beneficiaries (log) vs. management intensity, sized by dollars. Connecticut: 856 per 10k — 3× California — from just 122 clinicians (~190 patients each). Critical lens: the min-clinicians slider dissolves per-capita "leaders" into a handful of monitoring programs.

Data explorer

The Curve Payment Built

Source: FDA press announcement — first TEMPO participant selected: Dexcom (Jul 22, 2026) · MIMI Labs report + query: Medicare Physician & Other Practitioners, CPT 95249/50/51, 2013–2024

FDA just fused device oversight with a CMS payment path, and Dexcom is participant #1. Twelve years of Medicare CGM claims explain why that matters: the curve draws itself from 26,397 interpretation patients to 368,447 (14×), and every inflection lands on a coverage ruling — 2017 DME classification, 2021 fingerstick rule dropped, 2023 all-insulin expansion — never on a sensor launch. Meanwhile clinic-owned CGM peaked in 2018 and fell 66%. Critical lens: professional-fee sliver, FFS only — the levels understate, but the bends don't lie.

Graphical narrative
July 23, 2026

The Story Outran the Ledger

Sources: Olive funding and acquisition announcements · Axios · Fierce Healthcare · Becker's · Healthcare Dive · Waystar SEC filing

Walk two sourced tracks through Olive AI's expansion and contraction, then classify your own twenty-case shadow-mode sample to expose the exceptions a platform demo hides.

Interactive autopsy · ~4 min
July 20, 2026

The Map Under Subpoena

Source: HIT Doc (John Lee, MD) — "The Texas v. Epic story isn't the state's" (Jul 2026) · CMS Promoting Interoperability hospital attestations, PY2023; extract 2025-05-01 · MimiLabs SQL

Five Epic competitors refused discovery in unison — and while the real map of EHR data control gets assembled under subpoena, its public v0 is explorable now: 4,593 attesting hospitals, one dot per state, vendor share vs. market size, switchable across seven vendors. Epic: 40% of buildings, #1 in 34 of 56 states — and California is decided by one hospital (124 vs. 123). Critical lens: buildings ≠ beds ≠ records, and the min-hospitals slider dissolves Delaware's "57% Epic" (n=7) on contact.

Data explorer

The Breach Beat Is Background Noise

Source: Reuters — US companies face rise in cyber attacks (Jul 17, 2026) · HHS OCR breach portal, extract 2025-12-10 · MimiLabs SQL

Two more breach disclosures landed in one wire-service factbox this week and barely registered. Here's the numbness, quantified: 6,501 large-breach reports since the wall of shame opened in 2009, replayed month by month — from one every 44 hours (2010) to one every 12 (2023), 625M individuals, ~1.8× the US population. Critical lens: the biggest breach in history (Change Healthcare, 192.7M) still isn't in the confirmed archive — toggle the pending list on and "quiet" 2024 becomes the worst year ever recorded (~289M).

Graphical narrative
July 19, 2026

1.6 Million Former First-Years

Source: Daily Stoic — "6 Stoic Rules To Beat Ego" (Jul 18, 2026) · CMS Doctors & Clinicians National Downloadable File, extract 2026-06-01 · mimi_ws_1.provdatacatalog.dac_ndf via MIMI Labs

Companion to today's essay on why looking stupid is the price of building: every Medicare-enrolled clinician in America by medical-school graduation year — 1,608,842 people, one histogram, brushable by cohort, filterable by the 30 largest specialties (cardiology's median clinician is 27 years out; NPs, 8). Median clinician: 15 years past year one; 16.4% are in their first five years right now. Critical lens: the right-edge cliff is Medicare enrollment lag, not fewer graduates — brush 2024–2026 and don't believe your eyes.

Data explorer

Beginners Ship

Source: Daily Stoic — "6 Stoic Rules To Beat Ego" (Jul 18, 2026) · FDA 510(k) database, extract 2026-07-13 · mimi_ws_1.fda.device_510k via MIMI Labs

Since 1976, 25,351 organizations have cleared an FDA device — and every year ~500 more clear their first. In 2024, 43% of all clearing companies were first-timers. Animated 50-year chart of first attempts, plus the "beginner tax" by decade: first-timers pay ~32 extra days of median review in the 2020s, and ship anyway. Critical lens: name-based matching inflates "first-timers," 510(k) is the substantially-equivalent lane, and cleared-only data hides the beginners who never made it.

Graphical narrative
July 18, 2026

The Denial Economy's Public Ledger

Source: Healthcare Dive — W&M advances MLR Transparency Act 42-0 (Jul 17, 2026) · CMS Part C & D MLR filings, CY2023, extract 2023-12-31 · mimi_ws_1.partcd.mapd_mlr via MIMI Labs

Congress voted 42–0 to force MA plans to show how much revenue reaches patient care. The ledger it wants to open already has a public v0: every MA and Part D contract's 2023 MLR filing — 635 contracts, one dot each, enrollment (log) vs. adjusted MLR, sized by revenue, red below the 85% floor. $537.8B in, $52.4M paid back: 0.01%. Critical lens: the extreme ratios dissolve above 10,000 enrollees (small-contract artifacts) — and a denied claim is structurally invisible in this file, which is why denial-rate disclosure is the dataset that would actually change behavior.

Data explorer

The Appeal Nobody Files

Source: KFF — MA prior-auth denials for post-acute care (Jul 2026) · denial 65%/54%/12%, appeals 18%, overturns 95%

Congress voted on prior auth twice this week and took both sides on AI — but the decisive number sits in a KFF data brief: 95% of appealed SNF denials are overturned, and only 18% are ever appealed. Watch 100 denials play out as an animated dot field — 18 turn navy, 17 flip green, and dashed rings mark the ~78 of the silent 82 that would likely have been approved. Critical lens: filed appeals are plausibly the strongest cases, so ~78 is an upper bound — the honest claim is still damning.

Graphical narrative
July 17, 2026

The Landing Zone

Source: CMS — Proposed Transformational Medicare Reforms, CY2027 PFS rule (Jul 2026) · CMS Shared Savings Program PY2024, extract 2025-09-29 · MimiLabs SQL

CMS proposed giving traditional MIPS a 2029 expiration date and pointing clinicians at ACOs. Here's the destination: all 476 PY2024 MSSP ACOs, one dot each — beneficiaries (log) vs. savings rate, sized by earned dollars, navy for two-sided risk, red for one-sided. Filter by risk model, search any ACO, and drag the size floor. Critical lens: the 22% "miracle" savings rates dissolve above 20,000 beneficiaries (small-n variance), and 35 ACOs share an identical assigned quality score of 77.05.

Data explorer

The Report Card CMS Just Tore Up

Before the MIPS eulogies, the program's own report card: half a million clinician score records in one morphing distribution, told in four chapters — everyone scores 87, small practices carry 5× the penalty rate, 27% of solo/small records never reported (automatic −9%), and the average earned bonus was a rounding error. Critical lens: rows are TIN/NPI records, not people, and a saturated score can't tell a good clinician from a good billing department.

Graphical narrative
July 16, 2026

The Vendor Fingerprint

Source: STAT — CMS moves to ban remote patient monitoring vendors (Jul 15, 2026) · CMS Medicare Physician & Other Practitioners, CY2024 · via MIMI Labs

CMS proposed keeping the RPM codes and banning the third-party vendors who deliver the monitoring. Every state plotted by two fingerprints of that business model: billing concentration (patients per provider) vs. intensity (device-months per patient), sized by dollars. Toggle to $/patient and drag the sample-size floor. Critical lens: Connecticut's 189 patients/provider looks like a vendor factory but bills at low intensity — one big system, not churn. Traditional Medicare FFS only.

Data explorer

The Code That Outgrew Its Model

Source: STAT — CMS moves to ban remote patient monitoring vendors (Jul 15, 2026) · CMS Medicare Physician & Other Practitioners, CY2018–2024 · via MIMI Labs

Watch the RPM billing hockey stick draw itself — $1.2M in 2018 to $256M in 2024, a 210× run — with the RTM “escape valve” climbing off a tiny base, then the 2027 vendor ban. Critical lens: this FFS line is a floor (industry estimates near $500M add MA and cost-sharing), and the 2027 segment is a projection, not observed data.

Graphical narrative
July 15, 2026

The Public Road

Source: Delaware's Smart Health Network — the neutral state hub · ONC/ASTP AHA Annual Survey IT Supplement, 2024 wave · MimiLabs report + SQL

Delaware bet the health-data hub is public infrastructure; TEFCA is the national version of that bet. Fifty states plotted by hospitals surveyed vs. the share already live on the federal “connect once, reach everyone” network. Toggle to planning/any-network and drag the sample-size floor to watch the small-state leaders (Hawaii, 58% on 12 hospitals) dissolve. Self-reported survey awareness — not measured live-exchange volume.

Data explorer

Nine Billion Faxes, or One Road

Source: Delaware's Smart Health Network · ONC/ASTP AHA Annual Survey IT Supplement, 2024 wave · MimiLabs report + SQL

Watch the tangle of point-to-point “dirt tracks” (N×(N−1)/2 private lines) collapse into a single neutral hub (N). Then the real early road: 461 hospitals live on TEFCA, while 1,106 are still only planning. Critical lens: planning isn't plumbing, and Delaware itself is n=4.

Graphical narrative
July 14, 2026
July 13, 2026

The Machine That Saves Billions

Source: MedCity News — “Prior Auth Is a Fight and AI Won't End It” (Jul 2026) · CMS Medicare Advantage MLR 2023 · via MIMI Labs

Today's Big Thing says AI can't “end” prior auth because no payer unplugs a machine that saves it billions. Here's the machine: 571 real MA contracts, plotted by enrollment vs. medical loss ratio — the share of premium kept out of claims. The giants cluster right above the 85% federal floor and kept $40B between them; the industry kept $57.3B. Light up the billion-dollar valves, then drag the sample-size floor and watch the “some plans keep 25 cents” outliers dissolve into small-n noise.

Data explorer

The Denials Nobody Fought

In 2023 MA plans denied 3.2 million of ~50 million prior-auth requests. In 1,000 dots: reveal the 6.4% denied, then re-base the field to the denials and follow them — 88% were never appealed, and of the 12% that were, 82% got overturned. The denials that stuck, stuck mostly because nobody fought them. Critical lens: the 82% overturn rate ranges 42% (Kaiser) to 94% (Centene), and the 6.4% average hides far higher post-acute denials.

Graphical narrative
July 12, 2026

The 2 AM Distribution

Today's essay: the imagination that builds the tool is the same one that watches it kill someone at 2 AM — and it always renders the failure as a death. Each dot is one real drug in the FDA's 2026 Q1 adverse-event intake: serious-coded reports vs. the share that include death. Flip on the “2 AM version” (a red line at 100%) to see the gap, then drag the sample-size floor and watch the thin-sample outliers dissolve. Median reported death share: 11.4%.

Data explorer

What Anxiety Renders

1,000 real serious-coded drug-safety reports, laid out as a field. The 2 AM version is all red — every report a death, the way your imagination paints it. Press “show what actually gets logged” and the dots drain to their real outcomes while the counter falls from 100% to 14%. The critical lens: this view filters to outcome-coded cases, and spontaneous reporting still over-weights catastrophe.

Graphical narrative
July 11, 2026

Cleared, Then Unwatched

The FDA has cleared 1,451 AI-enabled devices; zero carry a mandatory post-market monitoring rule. Each dot is one real AI 510(k) clearance — year cleared vs. FDA review time, colored by specialty. Flip the switch to see what watches the device after go-live, and drag the sample-size floor to watch the “AI is diversifying beyond radiology” story dissolve into 1–3-device noise.

Data explorer

The 40% Nobody Logged

A cleared, validated CDS tool ran for six months with physicians silently overriding 40%+ of its recommendations — and no one noticed. Watch 100 recommendations resolve, navy for accepted, red for overridden, then reveal the monitoring layer that logged exactly zero of the reversals. Adoption is solved; the audit trail is the unbuilt product.

Graphical narrative
July 10, 2026

The Incidental Heart

Source: European Heart Journal – Digital Health (2026) · Dr. Ashley Beecy (Sutter Health)

34,000 paired chest CTs and echocardiograms. A model that finds reduced ejection fraction in scans ordered for lung nodules, cancer staging, and trauma — not the heart. Filter the scatter by scan indication, see where the model flags correctly, and explore the critical lens: this is a detection model, not a diagnostic. The business isn't the model — it's the “now what?” routing layer.

Data explorer

9.5 Million Patients, One Clearance

The Defense Health Agency just put ambient AI in every clinic it runs — 9.5M beneficiaries, ~400 clinics, one EHR. Documentation time at Wilford Hall dropped from 30–45 min to 5–10 min per note. Compare that to the JAMA multi-site average and your hospital's two-site pilot. The most security-obsessed buyer in American medicine just made ambient documentation infrastructure, not an experiment.

Graphical narrative
July 9, 2026

The Payable Sliver

Source: CMS SaMS interim payment policy (CY2027 OPPS) · CMS Medicare Physician & Other Practitioners

CMS just proposed the first payment lane for “Software as a Medical Service.” Before you build for it, see the one already open: 34 real HCPCS codes — remote monitoring, chronic-care management, e-visits — plotted by reach, pay-per-service and dollars. Step 2020→2024, drag the reach floor, and watch how few “software” lanes exist that don't just rent a clinician's minutes.

Data explorer

The Lane That Grew

Medicare remote-monitoring spend went 38× — $6.75M to $256M in five years — the moment the service got a code. Watch the curve climb, then meet the gap: 97% of doctors review wearable data, ≤6% have it integrated, because a consumer watch isn't the FDA device the lane requires. France had the code and still stalled.

Graphical narrative
July 3, 2026

The Override Nobody Uses

Source: KFF — ACA denials & appeals, 2024 · CMS Transparency in Coverage PUF

Every dot is one insurer: denial rate vs. how often the denial gets overturned on appeal, sized by claims volume. Drag the sample-size floor and watch the 80%+ "fairness" outliers dissolve into small-denominator noise. Insurers deny ~1 in 5 claims; patients appeal ~1 in 600 — but ~42% of appeals win. The override exists; almost nobody reaches it.

Data explorer

The Effect Vanishes

The most rigorous LLM decision-support trial yet cut clinician errors on chart review (−16% diagnostic, −13% treatment) — then showed no significant change in what happened to the patient 14 days later. Watch the gain decay, step by step, toward the bedside, and see the 19.5% action rate where the signal drains out.

Graphical narrative
July 2, 2026

The Real POCQi Explorer

A condensed scatter of all 30 specialties (drag the sample-size floor and watch the fake trend dissolve), plus a live OpenEvidence run showing why the hard half of point-of-care — building the question from a 1,200-document chart — never reaches the test set.

Data explorer
July 1, 2026

The Common Answer Trap

Companion to “Primary care declares independence”

A naive model reaches for the answer the internet gives most often. Play the model, then meet the patient the common answer would have hurt.

~3 min

The Verification Layer

Companion to “Primary care declares independence”

Build the checker that flags a confidently-common wrong answer before a human signs it. Discover why model confidence is the wrong signal to trust.

~3 min
June 30, 2026

Can You Survive the Rephrase?

Companion to “Health AI flunks the stress test”

Frontier AI models ace medical benchmarks — then break when the question is rephrased. See if you can do better.

~3 min

The Readiness Gap Simulator

Companion to “Health AI flunks the stress test”

Frontier AI models top the medical benchmark — then collapse under stress. Toggle the perturbations and watch the leaderboard reshuffle.

~3 min

The PERC Consistency Test

Experiment companion

20 runs. 3 models. 2 temperatures. One patient on Camila. Watch LLMs struggle with the estrogen trap hidden in prior visit notes.

~5 min